SQL

Related topics

• Gemini works with SQL From the official documentation: “Real-time analysis: brings the world knowledge of Gemini to enterprise data using SQL.”
• BigQuery works with SQL From the official documentation: “You can also use Cloud Asset Inventory to transfer this data into BigQuery. This will allow you to query the data using SQL, which is easier to read compared to interpreting JSON-formatted data.”
• SQL is part of Dimension From the official documentation: “Define a database table column in a LookML project once using the syntax `${TABLE}.field_name` in the dimension's `sql` parameter.”
• SQL is part of LookML From the official documentation: “The LookML [`sql`](/looker/docs/reference/param-field-sql) parameter”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Storage From the official documentation: “Sample to load Avro data from Cloud Storage into a new BigQuery table”
• BigQuery works with Data Studio From the official documentation: “Select the BigQuery [connector](/data-studio/connector).”
• BigQuery works with Looker From the official documentation: “Connect Looker to the BigQuery project.”
• BigQuery works with Knowledge Catalog From the official documentation: “Some Knowledge Catalog functionalities trigger job execution using BigQuery.”
• BigQuery ML works with Cloud Storage From the official documentation: “You can export BigQuery ML models to Cloud Storage, and use them for online prediction, or edit them in Python.”
• BigQuery works with Gemini From the official documentation: “Use Gemini to analyze your enterprise data in BigQuery.”
• BigQuery works with Vertex AI From the official documentation: “The page provides guidance for getting predictions from Vertex AI, based on retail [data exported into BigQuery](/retail/docs/export-data-into-bq).”
• LookML is part of Looker From the official documentation: “Get the dashboard's LookML content from enterprise Looker.”
• Cloud Storage works with Knowledge Catalog From the official documentation: “Knowledge Catalog is an intelligent governance solution for data and AI assets in Google Cloud. It provides a centralized inventory where you can discover, manage, and govern your data across Google Cloud data sources like BigQuery, Cloud Storage, Pub/Sub, and Spanner.”
• Data Studio works with Looker From the official documentation: “See the [Connecting to Data Studio](/looker/docs/looker-studio-connector) documentation page to learn more about connecting Looker and Data Studio.”
• BigQuery works with BigQuery ML From the official documentation: “BigQuery ML lets you build and operationalize machine learning (ML) models over data in BigQuery by using SQL.”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• BigQuery ML is part of BigQuery From the official documentation: “BigQuery ML models are stored in BigQuery datasets, similar to tables and views.”
• BigQuery ML depends on Cloud Storage From the official documentation: “BigQuery ML imports the model from Cloud Storage by using the credentials of the user who runs the `CREATE MODEL` statement.”
• BigQuery ML works with Gemini From the official documentation: “This tutorial shows you how to gain insights from unstructured image data by integrating BigQuery ML with Gemini.”
• Cloud Storage works with Gemini From the official documentation: “Perform batch text prediction with Gemini using GCS data source as input.”
• Cloud Storage works with Vertex AI From the official documentation: “Access Cloud Storage content through your current project's Vertex AI service agent.”
• Data Studio is an alternative to Looker From the official documentation: “You can also [export these recommendations to BigQuery](/recommender/docs/bq-export/export-recommendations-to-bq) and then examine them using [Data Studio](/bigquery/docs/visualize-looker-studio) or [Looker](/bigquery/docs/looker).”
• Dimension is part of Data Studio From the official documentation: “There are two types of fields in Data Studio: - **Dimensions** are your categories or labels.”
• Dimension is part of LookML From the official documentation: “The LookML [`dimension`](/looker/docs/reference/param-field-dimension) parameter”
• Gemini works with Knowledge Catalog From the official documentation: “**Chat powered by Gemini**: Powered by Gemini, the agent parses your natural language questions, runs search and metadata lookup tools against Knowledge Catalog, formulates multi-step exploration plans, and displays its progress in collapsible thought traces.”
• Gemini is part of Vertex AI From the official documentation: “Google Cloud provides a set of state-of-the-art foundation models through Vertex AI, including Gemini.”
• LookML configures Looker From the official documentation: “LookML tells Looker how to query data, so everyone in the organization can create easy-to-read reports and dashboards to explore patterns of data.”